Global summary

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively (see Methods or our paper for further explanation).

Using data available up to the: 2020-06-22

Note that it takes time for infection to cause symptoms, to get tested for SARS-CoV-2 infection, for a positive test to return and ultimately to enter the case data presented here. In other words, today’s case data are only informative of new infections about two weeks ago. This is reflected in the plots below, which are by date of infection.

Expected daily confirmed cases by country

Figure 1: The results of the latest reproduction number estimates (based on estimated confirmed cases with a date of infection on the 2020-06-11) can be summarised by whether confirmed cases are likely increasing or decreasing. This represents the strength of the evidence that the reproduction number in each region is greater than or less than 1, respectively (see the methods for details). Countries with fewer than 60 confirmed cases reported on a single day are not included in the analysis (light grey) as there is not enough data to reliably estimate the reproduction number.

Summary of latest reproduction number and confirmed case count estimates by date of infection

Figure 1: Confirmed cases with date of infection on the 2020-06-11 and the time-varying estimate of the effective reproduction number (light bar = 90% credible interval; dark bar = the 50% credible interval.). Regions are ordered by the number of expected daily confirmed cases and shaded based on the expected change in daily confirmedcases. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control and a single case required for elimination.

Reproduction numbers over time in the six regions expected to have the most new confirmed cases

Figure 2: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in the six regions expected to have the most new confirmed cases

Figure 3: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in the regions expected to have the highest number of new confirmed cases. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Reproduction numbers over time in all regions

Figure 4: Time-varying estimate of the effective reproduction number (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The horizontal dotted line indicates the target value of 1 for the effective reproduction no. required for control. The vertical dashed line indicates the date of report generation.

Confirmed cases and their estimated date of infection in all regions

Figure 5: Confirmed cases by date of report (bars) and their estimated date of infection (light ribbon = 90% credible interval; dark ribbon = the 50% credible interval) in all regions. Estimates from existing data are shown up to the 2020-06-11 from when forecasts are shown. These should be considered indicative only. Confidence in the estimated values is indicated by translucency with increased translucency corresponding to reduced confidence. The vertical dashed line indicates the date of report generation.

Latest estimates (as of the 2020-06-11)

Table 1: Latest estimates (as of the 2020-06-11) of the number of confirmed cases by date of infection, the effective reproduction number, and the doubling time (when negative this corresponds to the halving time) in each region. The mean and 90% credible interval is shown.

Country	New confirmed cases by infection date	Expected change in daily cases	Effective reproduction no.	Doubling/halving time (days)
Afghanistan	643 (582 – 694)	Unsure	1 (0.9 – 1.1)	340 (41 – -54)
Albania	61 (45 – 75)	Likely increasing	1.2 (1 – 1.4)	15 (6.9 – -96)
Algeria	123 (102 – 144)	Likely increasing	1.1 (0.9 – 1.2)	39 (13 – -40)
Andorra	5 (0 – 14)	Unsure	1.4 (0.1 – 3)	4 (1 – -2.7)
Argentina	1648 (1467 – 1814)	Increasing	1.2 (1.1 – 1.2)	16 (13 – 22)
Armenia	572 (521 – 630)	Increasing	1.1 (1 – 1.1)	36 (19 – 260)
Australia	21 (11 – 29)	Likely increasing	1.4 (1 – 1.8)	7.8 (3.8 – -70)
Austria	35 (23 – 45)	Unsure	1.1 (0.9 – 1.4)	22 (6.8 – -17)
Azerbaijan	394 (347 – 442)	Increasing	1.1 (1 – 1.2)	31 (16 – 560)
Bahrain	490 (435 – 541)	Unsure	1 (0.9 – 1.1)	-190 (48 – -32)
Bangladesh	3640 (3356 – 3907)	Increasing	1.1 (1.1 – 1.1)	29 (22 – 40)
Belarus	709 (641 – 764)	Likely decreasing	1 (0.9 – 1)	-99 (87 – -32)
Belgium	98 (76 – 114)	Likely decreasing	0.9 (0.8 – 1.1)	-36 (37 – -12)
Benin	41 (28 – 52)	Increasing	1.3 (1 – 1.7)	9.1 (4.7 – 86)
Bolivia	873 (784 – 957)	Increasing	1.2 (1.1 – 1.2)	18 (13 – 27)
Bosnia and Herzegovina	60 (44 – 74)	Likely increasing	1.2 (1 – 1.4)	20 (7.8 – -35)
Brazil	32653 (29114 – 35649)	Increasing	1.1 (1.1 – 1.2)	23 (18 – 31)
Bulgaria	94 (73 – 108)	Likely increasing	1.1 (1 – 1.3)	32 (11 – -35)
Cameroon	273 (228 – 315)	Unsure	1.1 (0.9 – 1.2)	67 (17 – -34)
Canada	402 (358 – 450)	Likely decreasing	0.9 (0.8 – 1)	-43 (120 – -18)
Central African Republic	97 (80 – 115)	Unsure	1.1 (0.9 – 1.2)	39 (11 – -28)
Chad	4 (0 – 8)	Unsure	1.1 (0.2 – 2)	13 (2 – -3.1)
Chile	10315 (9536 – 11290)	Increasing	1.3 (1.2 – 1.3)	11 (9.3 – 13)
China	41 (28 – 51)	Increasing	1.4 (1.1 – 1.7)	7.2 (4 – 28)
Colombia	2525 (2310 – 2768)	Increasing	1.2 (1.2 – 1.3)	12 (10 – 15)
Congo	34 (22 – 43)	Increasing	1.3 (1 – 1.6)	10 (4.8 – -95)
Costa Rica	72 (53 – 87)	Likely increasing	1.1 (1 – 1.3)	24 (9 – -36)
Cote dIvoire	284 (254 – 313)	Increasing	1.2 (1 – 1.3)	18 (11 – 50)
Croatia	9 (3 – 15)	Increasing	1.9 (1 – 2.9)	3.6 (1.8 – 170)
Cuba	14 (5 – 21)	Unsure	1.1 (0.7 – 1.6)	24 (4.6 – -7.8)
Czechia	71 (53 – 88)	Likely increasing	1.1 (0.9 – 1.3)	24 (8.9 – -34)
Democratic Republic of the Congo	142 (120 – 165)	Likely increasing	1.1 (1 – 1.2)	31 (12 – -58)
Denmark	39 (27 – 49)	Unsure	1.1 (0.8 – 1.3)	28 (8 – -18)
Djibouti	24 (12 – 33)	Decreasing	0.7 (0.4 – 0.9)	-9 (280 – -4.4)
Dominican Republic	500 (435 – 548)	Increasing	1.1 (1 – 1.1)	45 (21 – -260)
Ecuador	607 (549 – 659)	Increasing	1.1 (1 – 1.1)	35 (19 – 220)
Egypt	1621 (1504 – 1751)	Increasing	1.1 (1 – 1.1)	44 (27 – 120)
El Salvador	146 (125 – 167)	Increasing	1.2 (1 – 1.3)	16 (9.1 – 78)
Equatorial Guinea	54 (36 – 72)	Increasing	2 (1.5 – 2.6)	2.9 (2.1 – 4.8)
Estonia	4 (0 – 9)	Unsure	0.9 (0.3 – 1.5)	-9.8 (4.3 – -2.4)
Ethiopia	194 (167 – 215)	Likely increasing	1.1 (1 – 1.2)	56 (17 – -46)
Finland	10 (4 – 16)	Likely decreasing	0.8 (0.5 – 1.2)	-11 (13 – -3.9)
France	517 (449 – 576)	Likely increasing	1.1 (1 – 1.1)	32 (17 – 220)
Gabon	137 (112 – 156)	Increasing	1.2 (1.1 – 1.4)	11 (6.7 – 26)
Germany	528 (449 – 597)	Increasing	1.2 (1.1 – 1.3)	13 (9.3 – 21)
Ghana	352 (308 – 393)	Increasing	1.1 (1 – 1.2)	21 (13 – 60)
Greece	24 (14 – 33)	Unsure	1.1 (0.8 – 1.4)	59 (6.6 – -8.8)
Guatemala	499 (448 – 556)	Increasing	1.1 (1.1 – 1.2)	20 (13 – 42)
Guinea	72 (56 – 88)	Likely increasing	1.1 (0.9 – 1.3)	21 (8.7 – -49)
Guinea Bissau	17 (8 – 23)	Unsure	1.2 (0.8 – 1.6)	13 (4.5 – -14)
Haiti	132 (111 – 152)	Unsure	1 (0.8 – 1.1)	-58 (33 – -15)
Honduras	559 (476 – 631)	Increasing	1.3 (1.2 – 1.4)	11 (8.6 – 16)
Hungary	7 (2 – 11)	Likely decreasing	0.8 (0.4 – 1.2)	-9.3 (10 – -3.2)
Iceland	5 (0 – 8)	Likely increasing	2 (0.5 – 3.3)	3.3 (1.4 – -7.2)
India	13428 (12292 – 14526)	Increasing	1.1 (1.1 – 1.2)	22 (19 – 26)
Indonesia	1151 (1043 – 1260)	Increasing	1.1 (1 – 1.2)	31 (20 – 65)
Iran	2636 (2430 – 2830)	Increasing	1.1 (1 – 1.1)	32 (23 – 52)
Iraq	1512 (1360 – 1679)	Increasing	1.2 (1.1 – 1.2)	18 (14 – 27)
Ireland	15 (7 – 21)	Unsure	1 (0.6 – 1.3)	76 (6.4 – -7.6)
Israel	243 (204 – 279)	Increasing	1.2 (1.1 – 1.3)	16 (9.9 – 42)
Italy	266 (233 – 293)	Unsure	1 (0.9 – 1.1)	440 (28 – -32)
Japan	55 (40 – 67)	Likely increasing	1.1 (0.9 – 1.3)	24 (8.4 – -27)
Kazakhstan	403 (355 – 455)	Increasing	1.2 (1.1 – 1.3)	14 (9.6 – 23)
Kenya	148 (125 – 170)	Likely increasing	1.1 (0.9 – 1.2)	36 (13 – -48)
Kosovo	40 (28 – 51)	Likely increasing	1.3 (1 – 1.6)	11 (5.4 – -92)
Kuwait	557 (491 – 608)	Unsure	1 (0.9 – 1.1)	-140 (52 – -30)
Kyrgyzstan	124 (104 – 144)	Increasing	1.4 (1.1 – 1.6)	7.7 (5.2 – 14)
Latvia	6 (0 – 11)	Likely increasing	1.6 (0.5 – 2.7)	5.1 (1.8 – -5.9)
Lebanon	16 (7 – 23)	Unsure	1 (0.7 – 1.4)	380 (7 – -7.2)
Libya	18 (8 – 25)	Unsure	0.9 (0.6 – 1.2)	-17 (13 – -5.1)
Lithuania	8 (2 – 13)	Unsure	1.1 (0.5 – 1.5)	-100 (4.8 – -4.4)
Luxembourg	9 (3 – 14)	Likely increasing	1.4 (0.7 – 1.9)	8.7 (2.9 – -9.2)
Madagascar	39 (26 – 50)	Unsure	1.1 (0.8 – 1.3)	38 (7.9 – -14)
Malawi	19 (11 – 27)	Unsure	1.1 (0.8 – 1.4)	19 (5.4 – -12)
Malaysia	20 (11 – 27)	Likely decreasing	0.8 (0.5 – 1)	-29 (11 – -6.5)
Maldives	26 (15 – 35)	Unsure	1.1 (0.8 – 1.4)	19 (6 – -16)
Mali	25 (15 – 35)	Likely decreasing	0.8 (0.6 – 1.1)	-14 (31 – -5.7)
Mauritania	181 (154 – 203)	Increasing	1.3 (1.1 – 1.4)	11 (7.2 – 22)
Mexico	4884 (4522 – 5348)	Increasing	1.1 (1.1 – 1.1)	31 (24 – 43)
Moldova	386 (339 – 435)	Increasing	1.2 (1.1 – 1.3)	16 (11 – 32)
Mongolia	5 (0 – 9)	Likely increasing	1.9 (0.5 – 3.3)	3.2 (1.4 – -5.8)
Morocco	166 (139 – 194)	Increasing	1.3 (1.2 – 1.5)	8.8 (6 – 16)
Nepal	457 (422 – 497)	Increasing	1.1 (1 – 1.2)	21 (13 – 56)
Netherlands	139 (117 – 160)	Likely decreasing	0.9 (0.8 – 1)	-30 (81 – -13)
New Zealand	4 (0 – 8)	Likely increasing	2.3 (0.3 – 4)	2.3 (1 – -4.7)
Niger	10 (3 – 15)	Likely increasing	1.6 (0.8 – 2.3)	5.2 (2.3 – -26)
Nigeria	627 (560 – 700)	Increasing	1.1 (1.1 – 1.2)	21 (14 – 43)
North Macedonia	163 (140 – 183)	Likely increasing	1.1 (1 – 1.2)	42 (15 – -49)
Norway	18 (8 – 25)	Unsure	1.1 (0.7 – 1.5)	36 (5.6 – -8.1)
Oman	965 (904 – 1039)	Likely increasing	1.1 (1 – 1.1)	42 (23 – 270)
Pakistan	5800 (5475 – 6203)	Increasing	1 (1 – 1.1)	66 (42 – 150)
Palestine	47 (32 – 60)	Increasing	1.8 (1.4 – 2.3)	3.9 (2.7 – 7.3)
Panama	785 (701 – 864)	Increasing	1.2 (1.1 – 1.2)	17 (13 – 27)
Paraguay	16 (7 – 22)	Unsure	0.9 (0.6 – 1.2)	-21 (11 – -5.4)
Peru	4062 (3855 – 4290)	Decreasing	1 (0.9 – 1)	-79 (-540 – -43)
Philippines	608 (541 – 675)	Likely increasing	1.1 (1 – 1.1)	54 (23 – -140)
Poland	397 (356 – 439)	Unsure	1 (0.9 – 1.1)	-180 (41 – -28)
Portugal	357 (308 – 403)	Likely increasing	1.1 (1 – 1.2)	37 (17 – -170)
Puerto Rico	116 (97 – 133)	Unsure	1 (0.8 – 1.1)	-520 (20 – -19)
Qatar	1275 (1182 – 1361)	Decreasing	0.9 (0.9 – 1)	-39 (-100 – -24)
Romania	306 (265 – 344)	Increasing	1.2 (1.1 – 1.3)	14 (9.4 – 27)
Russia	8577 (8105 – 9165)	Likely increasing	1 (1 – 1)	210 (82 – -340)
Saudi Arabia	4561 (4244 – 4933)	Increasing	1.1 (1.1 – 1.2)	21 (18 – 27)
Senegal	111 (91 – 129)	Unsure	1 (0.9 – 1.2)	97 (16 – -24)
Serbia	84 (65 – 100)	Likely increasing	1.1 (0.9 – 1.3)	29 (10 – -36)
Sierra Leone	29 (18 – 39)	Unsure	1.1 (0.8 – 1.3)	72 (8.2 – -11)
Singapore	259 (227 – 287)	Decreasing	0.9 (0.8 – 0.9)	-21 (-76 – -12)
Slovakia	8 (2 – 13)	Likely increasing	1.6 (0.8 – 2.3)	6.1 (2.4 – -12)
Somalia	28 (18 – 38)	Likely decreasing	0.9 (0.6 – 1.1)	-17 (25 – -6.4)
South Africa	4005 (3676 – 4307)	Increasing	1.2 (1.1 – 1.2)	17 (14 – 20)
South Korea	51 (36 – 63)	Unsure	1.1 (0.9 – 1.3)	38 (9.3 – -18)
South Sudan	26 (16 – 35)	Likely decreasing	0.8 (0.6 – 1)	-10 (72 – -4.9)
Spain	368 (325 – 411)	Likely increasing	1.1 (1 – 1.1)	30 (16 – 310)
Sri Lanka	14 (7 – 21)	Unsure	1 (0.6 – 1.5)	29 (4.7 – -6.8)
Sudan	225 (198 – 250)	Increasing	1.1 (1 – 1.2)	22 (12 – 170)
Sweden	845 (778 – 901)	Likely decreasing	0.9 (0.9 – 1)	-81 (83 – -27)
Switzerland	36 (22 – 45)	Increasing	1.3 (1 – 1.6)	10 (5 – -1600)
Tajikistan	63 (47 – 76)	Likely decreasing	0.9 (0.8 – 1.1)	-40 (24 – -11)
Thailand	5 (1 – 10)	Unsure	1.3 (0.4 – 2.1)	9.5 (2.3 – -4.6)
Tunisia	11 (4 – 17)	Increasing	1.7 (0.9 – 2.4)	4.7 (2.3 – -97)
Turkey	1455 (1347 – 1555)	Increasing	1.1 (1.1 – 1.2)	19 (14 – 28)
Uganda	13 (5 – 19)	Unsure	0.9 (0.5 – 1.3)	-21 (7.6 – -4.4)
Ukraine	803 (724 – 887)	Increasing	1.2 (1.1 – 1.3)	14 (11 – 21)
United Arab Emirates	406 (359 – 447)	Decreasing	0.9 (0.8 – 1)	-30 (-240 – -16)
United Kingdom	1328 (1224 – 1428)	Unsure	1 (0.9 – 1)	360 (53 – -74)
United Republic of Tanzania	10 (3 – 15)	Decreasing	0.7 (0.4 – 1)	-8.4 (31 – -3.7)
United States of America	27470 (25218 – 29964)	Increasing	1.1 (1.1 – 1.2)	22 (19 – 27)
Uzbekistan	170 (148 – 193)	Increasing	1.1 (1 – 1.3)	21 (11 – 470)
Venezuela	127 (102 – 147)	Likely increasing	1.2 (1 – 1.3)	19 (9 – -200)
Yemen	38 (24 – 52)	Unsure	1 (0.8 – 1.3)	74 (8.7 – -11)
Zambia	20 (11 – 28)	Unsure	0.9 (0.6 – 1.2)	-26 (13 – -6.4)
Zimbabwe	23 (11 – 32)	Likely increasing	1.2 (0.9 – 1.6)	11 (4.5 – -21)